Setting a price — sound familiar?
Gabor-Granger tests real prices and finds the revenue-optimal one.
01 · DEMAND CURVE
See exactly where demand peaks.
Price acceptance curve, revenue index, and soft demand.
Respondents rate each price point as "Yes definitely", "Yes probably", "Not sure", "Probably not", or "Definitely not." Gabor-Granger plots definite demand, soft demand, and the revenue index (price × demand%) together — the intersection instantly shows the revenue-optimal price.
02 · DROP-OFF ANALYSIS
Find the highest price resistance zones.
Demand drop-off ranked by severity between each interval.
Between each pair of consecutive price points, Gabor-Granger calculates the absolute percentage-point drop and the relative change. Intervals are ranked from steepest to shallowest — the steepest drop shows where raising price triggers the sharpest volume loss, your key resistance zone.
Demand change between consecutive price points, sorted by severity.
03 · PRICE RANGE + ELASTICITY
Three strategic price points and interval elasticity.
Conservative, recommended, and premium tiers with elasticity table.
Skari derives three actionable price recommendations from the demand curve: the conservative volume-maximising price, the revenue-optimal point, and a premium tier for higher margin. An elasticity table shows whether each interval is elastic (demand sensitive) or inelastic (pricing headroom available).
04 · PRICE SEGMENTS
Who are your price-sensitive vs premium buyers?
Respondents classified as Price Sensitive, Value Seeker, or Premium Buyer.
Each respondent's maximum willing-to-pay price determines their segment. Skari shows the share and count for Price Sensitive (lowest WTP), Value Seeker (mid-range), and Premium Buyer (highest WTP) — giving you a direct read on whether your audience supports a premium tier.
Based on each respondent's maximum willing-to-pay price.
46.4% are Premium Buyers — a strong case for a premium tier priced at $99.
05 · CONFIDENCE INTERVALS
Know the statistical uncertainty behind every estimate.
Wilson 95% CI for each price point demand estimate.
At small sample sizes, demand estimates carry wide uncertainty. Skari shows Wilson score 95% confidence intervals for every price point alongside definite demand, soft demand, and the revenue index — so you can see whether the optimal price finding is statistically solid or directional only.
Wilson score 95% CI for each demand estimate.
| Price | n | Demand | 95% CI | Soft | Rev. index |
|---|---|---|---|---|---|
| $9 | 30 | 16.7% | 7.3–33.6% | 40% | 1.5 |
| $19 | 30 | 46.7% | 30.2–63.9% | 63.3% | 8.87 |
| $39 | 30 | 3.3% | 0.6–16.7% | 33.3% | 1.29 |
| $69Optimal | 30 | 80% | 62.7–90.5% | 83.3% | 55.2 |
| $99 | 30 | 43.3% | 27.4–60.8% | 56.7% | 42.87 |
IN THE REPORT
Everything Gabor-Granger delivers.
A few price points in — a full pricing report out.
Demand curve
Purchase intent at each tested price, plotted end to end.
Revenue index
Price × demand — the revenue-optimal point marked automatically.
Drop-off analysis
Where raising the price loses the most buyers.
Price elasticity
Interval-by-interval elasticity — elastic vs inelastic zones.
Strategic price points
Conservative, recommended, and premium price options.
Buyer segments
Price-sensitive, value seeker, and premium buyers with their optimal prices.
Confidence intervals
95% Wilson score CIs with a low-sample (n < 30) warning.
Recommended price
The best revenue row highlighted, with a decision-confidence read.
Auto interpretation
Every result comes with a plain-language reading.
From price question to optimal strategy.
Demand curve, drop-off zones, elasticity, buyer segments, and CI table — in one automated workflow.